Video frame interpolation techniques, which are also referred to as motion compensation techniques, generally involve the determination of motion vectors for changes between subsequent frames received from a video source. These motion vectors can then be used to generate intermediate frames by interpolating the motion of the video between successive video frames received from the video source. Video frames involving certain types of motion, such as object rotation or revolution, can be particularly problematic.
Phase plane correlation (PPC) methods can provide improved motion vectors for successive frames that involve translational motion. PPC methods also offer improved motion vectors in situations where there are changes in scene brightness such as a camera flash, for example. While PPC methods can be used to generate a good initial value of a motion vector for searching methods, these methods tend to be affected by repetitive patterns in the generated motion vectors.
Three-dimensional (3D) recursive methods can provide better motion vectors for non-translational motion with good spatial and temporal MV smoothness, but they have their own shortcomings as well. For example, the convergence of a motion vector using standard 3D recursive methods can vary drastically depending on the time and other factors specific to the situation.
Accordingly, there remains a need for improved motion vector determination in connection with video frame interpolation techniques.